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Diab M, Kumaraswamy N, Reece GP, Hanson SE, Fingeret MC, Markey MK, Ravi-Chandar K. Characterization of human female breast and abdominal skin elasticity using a bulge test. J Mech Behav Biomed Mater 2020; 103:103604. [PMID: 32090931 DOI: 10.1016/j.jmbbm.2019.103604] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 11/15/2019] [Accepted: 12/20/2019] [Indexed: 11/19/2022]
Abstract
Characterization of material properties of human skin is required to develop a physics-based biomechanical model that can predict deformation of female breast after cosmetic and reconstructive surgery. In this paper, we have adopted an experimental approach to characterize the biaxial response of human skin using bulge tests. Skin specimens were harvested from breast and abdominal skin of female subjects who underwent mastectomy and/or reconstruction at The University of Texas MD Anderson Cancer Center and who provided informed consent. The specimens were tested within 2 h of harvest, and after freezing for different time periods but not exceeding 6 months. Our experimental results show that storage in a freezer at -20 °C for up to about 40 days does not lead to changes in the mechanical response of the skin beyond statistical variation. Moreover, displacement at the apex of the bulged specimen versus applied pressure varies significantly between different specimens from the same subject and from different subjects. The bulge test results were used in an inverse optimization procedure in order to calibrate two different constitutive material models - the angular integration model proposed by Lanir (1983) and the generalized structure tensor formulation of Gasser et al. (2006). The material parameters were estimated through a cost function that penalized deviations of the displacement and principal curvatures at the apex. Generally, acceptable fits were obtained with both models, although the angular integration model was able to fit the curvatures slightly better than the Gasser et al. model. The range of the model parameters has been extracted for use in physics-based biomechanical models of the breast.
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Affiliation(s)
- Mazen Diab
- Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin, Austin, TX, USA; Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
| | - Nishamathi Kumaraswamy
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Gregory P Reece
- Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Summer E Hanson
- Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michelle C Fingeret
- Department of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mia K Markey
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Krishnaswamy Ravi-Chandar
- Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin, Austin, TX, USA
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Ozkan E, Goksel O. Compliance boundary conditions for patient-specific deformation simulation using the finite element method. Biomed Phys Eng Express 2018. [DOI: 10.1088/2057-1976/aa918d] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Sturgeon GM, Kiarashi N, Lo JY, Samei E, Segars WP. Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation. Med Phys 2017; 43:2207. [PMID: 27147333 DOI: 10.1118/1.4945275] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
PURPOSE The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. METHODS This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. RESULTS The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. CONCLUSIONS The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast.
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Affiliation(s)
- Gregory M Sturgeon
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705
| | - Nooshin Kiarashi
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708
| | - Joseph Y Lo
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705; and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708
| | - E Samei
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705; Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708; and Department of Physics, Duke University, Durham, North Carolina 27708
| | - W P Segars
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
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Hipwell JH, Vavourakis V, Han L, Mertzanidou T, Eiben B, Hawkes DJ. A review of biomechanically informed breast image registration. Phys Med Biol 2016; 61:R1-31. [PMID: 26733349 DOI: 10.1088/0031-9155/61/2/r1] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Breast radiology encompasses the full range of imaging modalities from routine imaging via x-ray mammography, magnetic resonance imaging and ultrasound (both two- and three-dimensional), to more recent technologies such as digital breast tomosynthesis, and dedicated breast imaging systems for positron emission mammography and ultrasound tomography. In addition new and experimental modalities, such as Photoacoustics, Near Infrared Spectroscopy and Electrical Impedance Tomography etc, are emerging. The breast is a highly deformable structure however, and this greatly complicates visual comparison of imaging modalities for the purposes of breast screening, cancer diagnosis (including image guided biopsy), tumour staging, treatment monitoring, surgical planning and simulation of the effects of surgery and wound healing etc. Due primarily to the challenges posed by these gross, non-rigid deformations, development of automated methods which enable registration, and hence fusion, of information within and across breast imaging modalities, and between the images and the physical space of the breast during interventions, remains an active research field which has yet to translate suitable methods into clinical practice. This review describes current research in the field of breast biomechanical modelling and identifies relevant publications where the resulting models have been incorporated into breast image registration and simulation algorithms. Despite these developments there remain a number of issues that limit clinical application of biomechanical modelling. These include the accuracy of constitutive modelling, implementation of representative boundary conditions, failure to meet clinically acceptable levels of computational cost, challenges associated with automating patient-specific model generation (i.e. robust image segmentation and mesh generation) and the complexity of applying biomechanical modelling methods in routine clinical practice.
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Affiliation(s)
- John H Hipwell
- Centre for Medical Image Computing, Malet Place Engineering Building, University College London, Gower Street, London WC1E 6BT, UK
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Ou Y, Weinstein SP, Conant EF, Englander S, Da X, Gaonkar B, Hsieh MK, Rosen M, DeMichele A, Davatzikos C, Kontos D. Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy. Magn Reson Med 2014; 73:2343-56. [PMID: 25046843 DOI: 10.1002/mrm.25368] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Revised: 05/28/2014] [Accepted: 06/24/2014] [Indexed: 02/02/2023]
Abstract
PURPOSE To evaluate DRAMMS, an attribute-based deformable registration algorithm, compared to other intensity-based algorithms, for longitudinal breast MRI registration, and to show its applicability in quantifying tumor changes over the course of neoadjuvant chemotherapy. METHODS Breast magnetic resonance images from 14 women undergoing neoadjuvant chemotherapy were analyzed. The accuracy of DRAMMS versus five intensity-based deformable registration methods was evaluated based on 2,380 landmarks independently annotated by two experts, for the entire image volume, different image subregions, and patient subgroups. The registration method with the smallest landmark error was used to quantify tumor changes, by calculating the Jacobian determinant maps of the registration deformation. RESULTS DRAMMS had the smallest landmark errors (6.05 ± 4.86 mm), followed by the intensity-based methods CC-FFD (8.07 ± 3.86 mm), NMI-FFD (8.21 ± 3.81 mm), SSD-FFD (9.46 ± 4.55 mm), Demons (10.76 ± 6.01 mm), and Diffeomorphic Demons (10.82 ± 6.11 mm). Results show that registration accuracy also depends on tumor versus normal tissue regions and different patient subgroups. CONCLUSIONS The DRAMMS deformable registration method, driven by attribute-matching and mutual-saliency, can register longitudinal breast magnetic resonance images with a higher accuracy than several intensity-matching methods included in this article. As such, it could be valuable for more accurately quantifying heterogeneous tumor changes as a marker of response to treatment.
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Affiliation(s)
- Yangming Ou
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Susan P Weinstein
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Emily F Conant
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sarah Englander
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Xiao Da
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bilwaj Gaonkar
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Meng-Kang Hsieh
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Angela DeMichele
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Patient-Specific Modeling of Breast Biomechanics with Applications to Breast Cancer Detection and Treatment. PATIENT-SPECIFIC MODELING IN TOMORROW'S MEDICINE 2011. [DOI: 10.1007/8415_2011_92] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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